Evidence map›Paper›PMID 35388370›Full record

ArticleBiology methods & protocols2022

PSSMCOOL: a comprehensive R package for generating evolutionary-based descriptors of protein sequences from PSSM profiles.

Alireza Mohammadi, Javad Zahiri, Saber Mohammadi, Mohsen Khodarahmi, Seyed Shahriar Arab

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Article in Biology methods & protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

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13citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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  10. ProkDBP: Toward more precise identification of prokaryotic DNA binding proteins.Protein science : a publication of the Protein Society · 2024
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Alireza MohammadiBioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran 14115111, Iran.
Javad ZahiriDepartment of Neuroscience, University of California San Diego, San Diego, CA 92093, USA.ORCID https://orcid.org/0000-0002-8360-2458
Saber MohammadiBioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran 14115111, Iran.ORCID https://orcid.org/0000-0002-9218-1616
Mohsen KhodarahmiDepartment of Radiology, Shahid Madani Hospital, Karaj 44693, Iran.
Seyed Shahriar ArabDepartment of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran 14115111, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Position-specific scoring matrix (PSSM), also called profile, is broadly used for representing the evolutionary history of a given protein sequence. Several investigations reported that the PSSM-based feature descriptors can improve the prediction of various protein attributes such as interaction, function, subcellular localization, secondary structure, disorder regions, and accessible surface area. While plenty of algorithms have been suggested for extracting evolutionary features from PSSM in recent years, there is not any integrated standalone tool for providing these descriptors. Here, we introduce PSSMCOOL, a flexible comprehensive R package that generates 38 PSSM-based feature vectors. To our best knowledge, PSSMCOOL is the first PSSM-based feature extraction tool implemented in R. With the growing demand for exploiting machine-learning algorithms in computational biology, this package would be a practical tool for machine-learning predictions.

Indexed as

feature extractionmachine learningPSSMR package

Identifiers

PMID35388370
PMCPMC8977839

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.